Add pipeline tag and library name

This PR improves the model card by adding the `pipeline_tag`, ensuring people can find your model at https://huggingface.co/models?pipeline_tag=image-text-to-text&sort=trending and `library_name`, enabling the "how to use" button, as well as a link to the project page and the Github repository.

README.md

@@ -1,14 +1,14 @@
 ---
-license: cc-by-nc-4.0
 datasets:
 - AGI-Eval-Official/Q-Eval-100K
 language:
 - en
+license: cc-by-nc-4.0
 arxiv: 2503.02357
+pipeline_tag: image-text-to-text
+library_name: transformers
 ---
 
-
-
 ### Model Description
 This model (Q-Eval-Score) is proposed in the paper "Q-Eval-100K: Evaluating Visual Quality and Alignment Level for Text-to-Vision Content". It is designed to comprehensively assess the quality and alignment of AI-generated visual content across both images and videos.
 
@@ -16,4 +16,7 @@ The model provides evaluation in four key dimensions:
 - Text-Image Alignment Evaluation: A model for assessing the alignment between AI-generated images and their corresponding textual descriptions.
 - Image Quality Evaluation: A model dedicated to evaluating the perceptual quality of AI-generated images.
 - Text-Video Alignment Evaluation: A model for measuring the alignment between AI-generated videos and their associated textual descriptions.
-- Video Quality Evaluation: A model focused on evaluating the visual quality of AI-generated videos.
+- Video Quality Evaluation: A model focused on evaluating the visual quality of AI-generated videos.
+
+Project page: https://zzc-1998.github.io/Q-Eval-100K/
+Code is available at https://github.com/zzc-1998/Q-Eval